On January 5, a group of imageomics students and faculty arrived at Mpala Research Centre in Kenya to conduct biological field research as part of the Experiential Introduction to Imageomics course. Students and faculty from The Ohio State University, Virginia Tech, Princeton, and Tulane University...
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Tanya Berger-Wolf is weaving biology and machine learning into a new field of science for wildlife conservation. By Ross Bishoff Her life’s work had been leading to this moment, this decision. Still, it was a hard decision. The timing was rocky. After years of leading wildlife conservation efforts...
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illustration of bird guide laid over background of countless photographs

Images as the source of information about life

Biologists must analyze traits in order to understand the significance of patterns in the two billion-year evolutionary history of life and to predict future effects of environmental change or genetic manipulation. Images are by far the most abundant source of documentation of life on the planet—but traits of organisms cannot be readily extracted from them.

The question: How do we take hundreds of thousands of images and use them to answer fundamental biological questions about ecology and evolution? At the very least, how do we extract traits, such as the example of a bird guide?

The answer: We make traits computable. Biology meets machine learning and vice versa.

Introducing imageomics (NSF OAC-2118240)

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